Statistical analysis of spatial and spatio-temporal point patterns /
by Diggle, Peter,
Series: Monographs on statistics and applied probability ; . 128 Edition statement:Third edition. Published by : Lancaster University, (England, UK :) Physical details: xxxi, 267 pages : illustrations ; 24 cm. ISBN:9781466560239 (hbk.); 1466560231 (hbk.). Year: 2014| Item type | Current location | Call number | Status | Date due | Barcode |
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General Collection
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Kukum Library General Stacks | K 519.535 DIG (Browse shelf) | Available | 50823 |
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| K 519.5024658 IMA Modern business statistics / | K 519.502855369 LEV Statistics for managers using Microsoft Excel / | K 519.5076 BAR Sigma mathematics | K 519.535 DIG Statistical analysis of spatial and spatio-temporal point patterns / | K 519.535 TAB Using multivariate statistics / | K 519.538 HOJ Graphical models with R / | K 519.55 BRO Introduction to time series and forecasting / |
"A Chapman & Hall book."
Includes bibliographical references (pages 245-262) and index.
Preliminary testing -- Methods for sparsely sampled patterns -- Spatial point processes -- Nonparametric methods -- Models -- Model-fitting using summary descriptions -- Model-fitting using likelihood-based methods -- Point process methods in spatial epidemiology -- Spatio-temporal point processes -- Exploratory analysis -- Empirical models and methods -- Mechanistic models and methods.
Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author's website --
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